---
license: other
tags:
- vision
- image-segmentation
- generated_from_trainer
model-index:
- name: parking-utcustom-train-SF-RGB-b5_2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# parking-utcustom-train-SF-RGB-b5_2

This model is a fine-tuned version of [nvidia/mit-b5](https://huggingface.co/nvidia/mit-b5) on the sam1120/parking-utcustom-train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1577
- Mean Iou: 0.4996
- Mean Accuracy: 0.9992
- Overall Accuracy: 0.9992
- Accuracy Unlabeled: nan
- Accuracy Parking: nan
- Accuracy Unparking: 0.9992
- Iou Unlabeled: nan
- Iou Parking: 0.0
- Iou Unparking: 0.9992

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 120

### Training results

| Training Loss | Epoch | Step | Validation Loss | Mean Iou | Mean Accuracy | Overall Accuracy | Accuracy Unlabeled | Accuracy Parking | Accuracy Unparking | Iou Unlabeled | Iou Parking | Iou Unparking |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-------------:|:----------------:|:------------------:|:----------------:|:------------------:|:-------------:|:-----------:|:-------------:|
| 0.767         | 20.0  | 20   | 0.6634          | 0.3299   | 0.9898        | 0.9898           | nan                | nan              | 0.9898             | 0.0           | 0.0         | 0.9898        |
| 0.5036        | 40.0  | 40   | 0.3752          | 0.3316   | 0.9949        | 0.9949           | nan                | nan              | 0.9949             | 0.0           | 0.0         | 0.9949        |
| 0.3486        | 60.0  | 60   | 0.2976          | 0.3319   | 0.9958        | 0.9958           | nan                | nan              | 0.9958             | 0.0           | 0.0         | 0.9958        |
| 0.2729        | 80.0  | 80   | 0.2355          | 0.3326   | 0.9978        | 0.9978           | nan                | nan              | 0.9978             | 0.0           | 0.0         | 0.9978        |
| 0.2246        | 100.0 | 100  | 0.1822          | 0.4983   | 0.9966        | 0.9966           | nan                | nan              | 0.9966             | nan           | 0.0         | 0.9966        |
| 0.2131        | 120.0 | 120  | 0.1577          | 0.4996   | 0.9992        | 0.9992           | nan                | nan              | 0.9992             | nan           | 0.0         | 0.9992        |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu117
- Datasets 2.13.1
- Tokenizers 0.13.3